Exercise 1. Using classical statistics describe the structure of monthly turnover of 80 shops [in tousand PLN].Calculate and interpret: arithmetic mean, standard deviation, coefficient of variability, coefficient of asymmetry (skewness) and coefficient of concentration (kurtosis).
Exercise 1. Using classical statistics describe the structure of monthly turnover of 80 shops [in tousand PLN].Calculate and interpret: arithmetic mean, standard deviation, coefficient of variability, coefficient of asymmetry (skewness) and coefficient of concentration (kurtosis).
Exercise 2. Using positional statistics describe the structure of monthly turnover of 80 shops [in tousand PLN]Calculate and interpret: median, quartiles, deciles, quartile deviation, positional coefficient of variation, positional coefficient of asymmetry and positional coefficient of concentration.
Perform all calculations for the following data types:
- individual data,
- interval groupped data.
| 38 | 25 | 80 | 55 | 65 | 60 | 33 | 64 |
| 34 | 57 | 38 | 37 | 37 | 35 | 63 | 60 |
| 42 | 53 | 38 | 33 | 44 | 43 | 40 | 72 |
| 38 | 62 | 55 | 36 | 70 | 64 | 43 | 74 |
| 75 | 71 | 36 | 48 | 49 | 51 | 41 | 53 |
| 69 | 55 | 55 | 36 | 54 | 32 | 67 | 67 |
| 29 | 56 | 85 | 58 | 63 | 51 | 26 | 33 |
| 88 | 47 | 24 | 82 | 31 | 50 | 54 | 38 |
| 37 | 52 | 54 | 39 | 53 | 68 | 76 | 60 |
| 64 | 46 | 45 | 49 | 47 | 40 | 51 | 37 |
Exercise 3.
- Calculate Pearson's
correlation coefficient between expenditure (Y) and the income per 1 person (X). - Build a linear regression model describing the relationship between expenditure (Y) and income per 1 person (X):
- estimate the structural parameters of the regression model,
- interprete the regression coefficient,
- determine the theoretical values and residuals from the estimated model.
All measures should be interpreted. Accuracy of calculations - up to the thousandth. |
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